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A pragmatic evidence-based clinical management algorithm for burning mouth syndrome
BACKGROUND: Burning mouth syndrome is a poorly understood disease process with no current standard of treatment. The goal of this article is to provide an evidence-based, practical, clinical algorithm as a guideline for the treatment of burning mouth syndrome. MATERIAL AND METHODS: Using available e...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medicina Oral S.L.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937967/ https://www.ncbi.nlm.nih.gov/pubmed/29750091 http://dx.doi.org/10.4317/jced.54247 |
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author | Kim, Yohanan Yoo, Timothy Han, Peter Liu, Yuan Inman, Jared C. |
author_facet | Kim, Yohanan Yoo, Timothy Han, Peter Liu, Yuan Inman, Jared C. |
author_sort | Kim, Yohanan |
collection | PubMed |
description | BACKGROUND: Burning mouth syndrome is a poorly understood disease process with no current standard of treatment. The goal of this article is to provide an evidence-based, practical, clinical algorithm as a guideline for the treatment of burning mouth syndrome. MATERIAL AND METHODS: Using available evidence and clinical experience, a multi-step management algorithm was developed. A retrospective cohort study was then performed, following STROBE statement guidelines, comparing outcomes of patients who were managed using the algorithm and those who were managed without. RESULTS: Forty-seven patients were included in the study, with 21 (45%) managed using the algorithm and 26 (55%) managed without. The mean age overall was 60.4 ±16.5 years, and most patients (39, 83%) were female. Cohorts showed no statistical difference in age, sex, overall follow-up time, dysgeusia, geographic tongue, or psychiatric disorder; xerostomia, however, was significantly different, skewed toward the algorithm group. Significantly more non-algorithm patients did not continue care (69% vs. 29%, p=0.001). The odds ratio of not continuing care for the non-algorithm group compared to the algorithm group was 5.6 [1.6, 19.8]. Improvement in pain was significantly more likely in the algorithm group (p=0.001), with an odds ratio of 27.5 [3.1, 242.0]. CONCLUSIONS: We present a basic clinical management algorithm for burning mouth syndrome which may increase the likelihood of pain improvement and patient follow-up. Key words:Burning mouth syndrome, burning tongue, glossodynia, oral pain, oral burning, therapy, treatment. |
format | Online Article Text |
id | pubmed-5937967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Medicina Oral S.L. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59379672018-05-10 A pragmatic evidence-based clinical management algorithm for burning mouth syndrome Kim, Yohanan Yoo, Timothy Han, Peter Liu, Yuan Inman, Jared C. J Clin Exp Dent Research BACKGROUND: Burning mouth syndrome is a poorly understood disease process with no current standard of treatment. The goal of this article is to provide an evidence-based, practical, clinical algorithm as a guideline for the treatment of burning mouth syndrome. MATERIAL AND METHODS: Using available evidence and clinical experience, a multi-step management algorithm was developed. A retrospective cohort study was then performed, following STROBE statement guidelines, comparing outcomes of patients who were managed using the algorithm and those who were managed without. RESULTS: Forty-seven patients were included in the study, with 21 (45%) managed using the algorithm and 26 (55%) managed without. The mean age overall was 60.4 ±16.5 years, and most patients (39, 83%) were female. Cohorts showed no statistical difference in age, sex, overall follow-up time, dysgeusia, geographic tongue, or psychiatric disorder; xerostomia, however, was significantly different, skewed toward the algorithm group. Significantly more non-algorithm patients did not continue care (69% vs. 29%, p=0.001). The odds ratio of not continuing care for the non-algorithm group compared to the algorithm group was 5.6 [1.6, 19.8]. Improvement in pain was significantly more likely in the algorithm group (p=0.001), with an odds ratio of 27.5 [3.1, 242.0]. CONCLUSIONS: We present a basic clinical management algorithm for burning mouth syndrome which may increase the likelihood of pain improvement and patient follow-up. Key words:Burning mouth syndrome, burning tongue, glossodynia, oral pain, oral burning, therapy, treatment. Medicina Oral S.L. 2018-04-01 /pmc/articles/PMC5937967/ /pubmed/29750091 http://dx.doi.org/10.4317/jced.54247 Text en Copyright: © 2018 Medicina Oral S.L. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Kim, Yohanan Yoo, Timothy Han, Peter Liu, Yuan Inman, Jared C. A pragmatic evidence-based clinical management algorithm for burning mouth syndrome |
title | A pragmatic evidence-based clinical management
algorithm for burning mouth syndrome |
title_full | A pragmatic evidence-based clinical management
algorithm for burning mouth syndrome |
title_fullStr | A pragmatic evidence-based clinical management
algorithm for burning mouth syndrome |
title_full_unstemmed | A pragmatic evidence-based clinical management
algorithm for burning mouth syndrome |
title_short | A pragmatic evidence-based clinical management
algorithm for burning mouth syndrome |
title_sort | pragmatic evidence-based clinical management
algorithm for burning mouth syndrome |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937967/ https://www.ncbi.nlm.nih.gov/pubmed/29750091 http://dx.doi.org/10.4317/jced.54247 |
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